Datadog unifies the data from servers, databases, applications, tools and services to present a unified view of the infrastructure. These capabilities are provided on a SaaS-based monitoring and data analytics platform that enables multiple teams working collaboratively on the infrastructure to avoid downtime, resolve performance problems and ensure that development and deployment cycles finish on time.
In 2010, Olivier Pomel, and Alexis Lê-Quôc (at the time, the Directors of Development and Operations, respectively, at a large education SaaS company), found themselves spending more time keeping the peace between their divisions and trying to decipher results from their monitoring systems than doing actual IT work. It seemed as if the dev and ops teams were always at odds, stemming from constant confusion as to what was actually occurring within the IT infrastructure. Each team used different tools to monitor the same systems in order to gain the results that mattered to them. Unfortunately, getting to these conclusions meant that each team also collected different metrics from each system, gauged results on separate time scales and established widely varying criteria to measure their KPIs. To make matters even more perplexing, the multiple on-premise and cloud monitoring tools that the teams relied on were cumbersome to use and did not integrate together easily or seamlessly. The end result was a constant stream of conflicting data, calculations and goals that were quickly lost in translation between the two teams.
With no single source of truth, it was not surprising that confusion and disagreement were a constant in the IT department. Alexis and Olivier decided that there had to be a better way for dev and ops teams to jointly gain visibility into their infrastructure and to be able to collaborate. Thus, the concept behind Datadog was born: a system that would bring together system metrics, changes, alerts and events from across the infrastructure so that dev and ops teams each see their key data in a same pane of glass, and also collaborate together in real-time.
Moreover, Alexis and Olivier recognized that a monitoring solution should not just be something that was installed as an afterthought when problems began occurring, but rather, a component that should be proactively worked into every feature and infrastructural addition. Baking a monitoring component into each new IT initiative allows dev and ops teams to not only identify developing issues before they occur but also to optimize their code and the configuration for peak performance. In order to add monitoring to any component or data stream in minutes, Datadog was engineered to be effortless to implement across the infrastructure, flexible enough to adapt to unique circumstances and easy to use so that entire IT teams could be rapidly on boarded to work together off the same data.